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CORR
2008
Springer

Quickest Change Detection of a Markov Process Across a Sensor Array

8 years 2 months ago
Quickest Change Detection of a Markov Process Across a Sensor Array
Recent attention in quickest change detection in the multi-sensor setting has been on the case where the densities of the observations change at the same instant at all the sensors due to the disruption. In this work, a more general scenario is considered where the change propagates across the sensors, and its propagation can be modeled as a Markov process. A centralized, Bayesian version of this problem, with a fusion center that has perfect information about the observations and a priori knowledge of the statistics of the change process, is considered. The problem of minimizing the average detection delay subject to false alarm constraints is formulated as a partially observable Markov decision process (POMDP). Insights into the structure of the optimal stopping rule are presented. In the limiting case of rare disruptions, we show that the structure of the optimal test reduces to thresholding the a posteriori probability of the hypothesis that no change has happened. We establish th...
Vasanthan Raghavan, Venugopal V. Veeravalli
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where CORR
Authors Vasanthan Raghavan, Venugopal V. Veeravalli
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